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10/31/2014
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Leading Technologies in Microbial Identifications:
Genotypic and Proteotypic
Maximizing Accuracy and Efficiency
Christine Farrance, PhD Director of Research and Development Endotoxin and Microbial Detection | Charles River [email protected] | www.criver.com
• Risk Management and Environmental Monitoring of Microorganisms
• Analyzing your State of Control - Tracking and Trending
• Review of Microbial Identification Technologies
• Factors Impacting Accuracy and Reproducibility
• Maximizing Efficiencies and Decreasing Process Variability
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Presentation Agenda
Question: Why Do You ID Microbes?
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MANAGING RISK Close scrutiny by the FDA and other regulatory agencies keeps industry focused on effectively managing risk
Because…
Preventing contamination is critical to consumer safety and product efficacy
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Managing Risk
• Manufacturing processes are a series of steps which are interlinked and independent and all processes have variability
• Variability increases risk and lowers quality
• The goal is to understand, control and reduce variability
• Quality risk management is an important part of science-based decision making which is essential to manufacturing
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The Importance of Accurate Identifications
The Isolate of Concern
• Risk management – Evaluate level of risk
• Permits determination of the potential origin of contamination
• Is the isolate objectionable? – Adverse effect on the product
or the consumer
• CAPA planning to mitigate risk
The Environmental Monitoring Program
• Measures the state of control of the manufacturing facility
• Provides reliable and comprehensive information on the quality of the environment
• Acts as a surveillance, early warning, system
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Document consistent quality management and control
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Environmental Monitoring
Establishing an EM program is one of the most important components of an effective manufacturing production and process control system
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• The program should provide accurate information to measure the state of control of the manufacturing facility through the specific detection, identification and quantification of microorganisms
• The program should identify areas for continual improvement, and help understand and reduce process variability
• Apply risk management principles to the program to design processes to prevent contamination, investigate ways to correct contamination events and assess the potential impact of contamination events
Environmental Monitoring
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• Provides a baseline profile of a manufacturing environment
• Acts as an early warning system to detect possible environmental contaminants that are out of limits and that may impact the product
• Promptly identifies the sites at risk of contaminating the product
• Documents consistent quality and control
The value of viable microbial monitoring is realized when the data are used to identify and correct an unacceptable work practice.
Monitoring the State of Control Tracking and Trending
• The data gathered in a well-designed and executed EM program provides critical information for tracking and trending (T&T) on a routine basis
• Accurate and consistent species-level identifications will result in more confidence in the T&T information
• Any significant change in microbial flora can be considered in a review of the ongoing monitoring data and used in investigations of the excursion, affect the mitigation process and aid in root cause determination
• T&T provides a detailed analysis regarding the state of environmental control within the manufacturing area
– Detect the emergence of indicator organisms and – Allow excursions from normal operating conditions to be identified
quickly and reliably
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Trending Bacteria by Gram Reaction and Morphology
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Trending Species by Frequency of Occurrence Over Specified Time Period
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302 IDs from April – June 2014
Trending Specific Species Over Time
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Importance of Microbial Identities
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• Need to be able to accurately identify an organism to the species level, and many times, to the strain level
• Know the flora of your environment
• Know what is around and in your ingredients, components or product
• Establish limits on those types of contaminants that may adulterate your finished product
• Know if you have detected an objectionable organism
Microbiological identification platforms are available that can provide the analytical tools necessary to accomplish these tasks
with accuracy and repeatibility
The Evolution of Microbial Identification
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The identification of microorganisms can be done through different processes, each with its own level of accuracy
and reproducibility
Phenotypic ID – Biochemical Analysis
• Differentiate between organisms based on the results of biochemical tests such as sugar fermentation or physiological properties such as salt or pH tolerance, manual or automated systems
• Differentiate based on patterns of cellular fatty acids that are extracted, methylated and separated by gas chromatography to generate a fingerprint
Systems have been in use for decades
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Phenotypic Characterization
• These methods have a role in a microbial quality program, but need a prior accurate identification to utilize the information
• The results from phenotypic reactions can help determine the biochemical activity of an organism on the product and the resulting stability of the product in the presence of that organism
• Understanding the nutrient requirements of an organism can reduce risk by providing insight into controlling or eliminating the organism in the environment or preserving the product
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Genotypic DNA Sequence-Based
Proteotypic Protein Fingerprint-Based
Identifications are based on information contained
in the Ribosome
Ribosomal Structure
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Small Subunit Large Subunit
70S
50S 30S
16S rRNA 21 proteins
5S and 23S rRNAs 34 proteins
Bacterial Genome organization Bacterial Ribosome
SSU LSU
16S 5S 23S
ITS1 ITS2
SSU LSU
18S 5.8S 28S
ITS1 ITS2 D2
ETS
Fungal Genome organization
ITS2 (Internal Transcribed Spacer) is used by taxonomists for the ID of fungal species as it is more variable than other regions, providing more species level differentiation
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Genotypic Identifications
DNA Sequence-Based
• Genotypic identification methods involve sequencing different regions of the microorganisms’ ribosomal RNA genes (16S or ITS2), resulting in an identification to the species or occasionally the subspecies level
• Universal system for all microorganisms since rRNA ubiquitous in all organisms and functionally conserved as part of the ribosomal complex
• The use of ribosomal DNA sequences for the purposes of bacterial and fungal taxonomic classification has been in practice for many decades
Target for Genotypic Identification: Ribosomal RNA
• Highly conserved regions of sequence
• Highly variable regions
• Allowing for species level resolution
• Bacterial identification
• Taxonomy from ~1500 bases
• Identification from ~500 bases
• Information content is high
• Complexity is in the data
• High level of species discrimination
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1 GATGAACGCT GGCGGCGTGC TTAACACATG CAAGTCGAAC GATGAAGCCC AGCTTGCTGG
61 GTGGATTAGT GGCGAACGGG TGAGTAACAC GTGAGTAACC TGCCCTTAAC TCTGGGATAA
121 GCCTGGGAAA CTGGTCTAAT ACCGGATAGG AGCGTCCACC GCATGGTGGG TGTTGGAAAG
181 ATTTATCGGT TTTGGATGGA CTCGCGGCCT ATCAGCTTGT TGGTGAGGTA ATGGCTCACC
241 AAGGCGACGA CGGGTAGCCG GCCTGAGAGG GTGACCGGCC ACACTGGGAC TGAGACACGG
301 CCCAGACTCC TACGGGAGGC AGCAGTGGGG AATATTGCAC AATGGGCGCA AGCCTGATGC
361 AGCGACGCCG CGTGAGGGAT GACGGCCTTT CGGGTTGTAA ACCTCTTTCA GTAGGGAAGA
421 AGCGAAAGTG ACGGTACCTG CAGAAGAAGC ACCGGCTAAC TACGTGCCAG CAGCCGCGGT
481 AATACGTAGG GTGCGAGCGT TATCCGGAAT TATTGGGCGT AAAGAGCTCG TAGGCGGTTT
541 GTCGCGTCTG TCGTGAAAGT CCGGGGCTTA ACCCCGGATC TGCGGTGGGT ACGGGCAGAC
Sequence Data
Isolate DNA from a single, pure colony
PCR amplify target sequences and subject to cycle sequencing
Raw Sequence Electropherogram
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Genotypic Identification Methodology
Analyze, assemble and interpret the data utilizing the semi-automated reference method for the highest accuracy
Compare full length sequence to a comprehensive library for ID
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Genotypic Identification Methodology
When assigning taxonomic designation
• The genetic distance measure (% difference or similarity) and
• The branching order of the phylogenetic tree which indicates how all the organisms relate to one another
Are equally important in making the final identification and confidence determination
Proteotypic Identifications
Protein Fingerprinting-Based ID
• Identification method for utilizing matrix-assisted laser desorption/ionization – time of flight (MALDI-TOF) mass spectrometry
• High level of species discrimination
• High informational content in the assay (mass peaks)
• Rapid, accurate and reproducible
• A paradigm shift in routine identifications for EM programs
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MALDI-TOF Theory
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Matrix molecule Analyte molecules
laser
Theory and Instrument • MALDI-TOF MS
– Matrix-assisted laser desorption/ionization Time-of-Flight Mass Spectrometry
• Ion Source (MALDI)
• Mass Analyzer (TOF)
• Detector (SEM) • Secondary Electron Multiplier
• Analysis (Mass Spectra)
Process • Sample preparation – co-crystallization
• Ionization
• Electrode Acceleration
• Ionic Separation
• Detection
• Analysis
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MALDI-TOF Methodology
Escherichia coli
Enterobacter aerogenes
Bacillus niacini
Spectra Unknown (primarily ribosomal proteins) Sample Preparation
Sample Spotting
Spotted Target Plate MALDI-TOF analysis
Library Comparison
Identification
Normalized logarithmic value of: The number of peaks in the known library entry that match to peaks detected in the unknown sample. The number of peaks in the unknown sample that match to peaks in the known library entry. The symmetry of the intensity of peaks that match between the known library entry and unknown library entry.
Library Comparison – Peak Lists and Match Factors
Match Factor = 2.84
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MALDI-TOF and Microbial IDs
Match Factor = 1.56
Library Reference Entry: Brevundimonas diminuta
Library Reference Entry: Enterobacter aerogenes
Unknown Sample
• Visually see the Match Factor Score of the identified organism and its 10 next closest matches (green=species confidence level)
• Top Match Score is the identification
Identification Report
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Level of Resolution for ID Methods • Different technologies have varying degrees of resolution
• What level of resolution do you use? When? Why?
• “Genus-level is good enough”?
• “Species-level is overkill” for routine?
Family Genus Species Subspecies Strain
Protein Coding or Housekeeping Gene Sequencing
Ribosomal DNA Sequencing (16S, ITS2)
Ribotyping
Proteotypic Mass Spectrometry ID
Strain Typing
Phenotypic Biochemical
If the underlying causes of variation are understood and
controlled, there is a good shot at a long term, defect-free process
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What Are The Factors That Contribute To Process Variability?
• Information content to speciate unknown organisms
• Reference libraries and error rates – Outdated databases
– Limited coverage
– Clinical focus
• Method Variation – Phenotypic
– Genotypic
– Proteotypic
• Process Controls
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Ability of a System to Discriminate is Based on the Potential Information Content
Genotypic methods • 16S rDNA Sequencing, 460 bp informative, 4 bases…………..4+460 = 8 x 10+276
• Fragment technology 64 Fragment sizes, 10 levels .………….10+64 = 1 x 10+64
Proteotypic methods • MALDI-TOF, 700 Mass frag. sizes, yes/no……………………….…2+700 = 5 x 10+210
Phenotypic methods • Fatty Acids, 128 FAs, 4 quantitative levels…………………........4+128 = 1 x 10+77
• Carbon utilization, 95 tests, yes/no……….……………………….…2+95 = 4 x 10+28
• Biochemical, 40 tests, yes/no...………………………………………...2+40 = 1 x 10+12
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16S rDNA sequencing and mass spectrometry easily discriminate thousands of species
What Are The Factors That Contribute To Process Variability?
• Information content to speciate unknown organisms
• Reference libraries and error rates – Outdated databases
– Limited coverage
– Clinical focus
• Method Variation – Phenotypic
– Genotypic
– Proteotypic
• Process Controls
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Impact of the Reference Library
• Accuracy of an identification is dependent on the library against which you compare your data
• Relevant coverage - library should complement the source environment
• Manufacturing EM programs, as well as clinical and industrial isolates
• Insufficient library coverage impacts the number of reportable results
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1
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1,000
10,000
1 501 1001 1501 2001 2501
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Library Comparison – 16S FOO
90% 95% 99% 100%
n = 987
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Represented in the OEM Library
Not Represented in the OEM Library
55% of most frequently identified bacteria are contained in the OEM Library
n = 85,557 Species Count
Log
(Fre
qu
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of
Occ
urr
ence
)
What Diversity is Needed?
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Represented in the OEM Library
Not Represented in the OEM Library1
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1,000
10,000
1 251 501 751 1001
90% 95% 99% 100%
Library Comparison – ITS FOO
16% of the most frequently identified fungi are contained in the OEM Library
n = 25,930 Species Count
n = 446
Log
(Fre
qu
ency
of
Occ
urr
ence
)
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What Diversity is Needed?
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40
60
80
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Yeast MoldMushroom
N/A
Pe
rcen
t
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20
40
60
80
100
Yeast MoldMushroom
N/A
Pe
rcen
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ITS OEM Library
Species and type of fungi contained in the OEM library are not representative of the most frequently encountered fungi observed
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n = 446
What Distribution is Needed?
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10
100
1,000
10,000
1 251 501 751 1001
90% 95% 99% 100%
Library Comparison – ITS FOO
n = 25,930 Species Count
Log
(Fre
qu
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Occ
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What Are The Factors That Contribute To Process Variability?
• Information content to speciate unknown organisms
• Reference libraries and error rates – Outdated databases
– Limited coverage
– Clinical focus
• Method Variation – Phenotypic
– Genotypic
– Proteotypic
• Process Controls
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Process Variability - Phenotypic
• Requires live, healthy organism
• Manual systems - labor intensive
• Automated systems have limited process control checks
• May or may not need to be cultured on specific media and at specific temperatures
• May or may not require ancillary testing such as Gram stain to achieve an identification
• Limited system complexity with limited databases
• Can have subjective interpretation of the test results and thus a higher rate of inaccurate or inconsistent identifications
• Microorganisms isolated from manufacturing environments will likely be physiologically stressed and may not fully express their phenotypic or biochemical characteristics resulting in erroneous ID or no ID
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• Genotypic Methods
– DNA extraction, amplification and sequencing reactions (multiple sample preparation steps) • DNA concentrations, reagents, clean-ups
– Instrumentation (thermocycler, sequencer, pipettes)
– Data/sequence quality, polymorphic positions
– Transcription/technician errors
– May require additional tests for an ID
– Limited and non-relevant reference libraries to make the ID
Process Variability - Genotypic
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• MALDI-TOF Methods
– All require a live, healthy organism
– Temperature exposure and age of culture
– Sample preparation
– Transcription/technician errors
– May require additional tests for an ID
– Limited and non-relevant reference libraries to make the ID
Process Variability - Proteotypic
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What Are The Factors That Contribute To Process Variability?
• Information content to speciate unknown organisms
• Reference libraries and error rates – Outdated databases
– Limited coverage
– Clinical focus
• Method Variation – Phenotypic
– Genotypic
– Proteotypic
• Process Controls
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Minimizing Process Variability through Six Sigma and Theory of Constraints
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• Six Sigma focuses on variation and design
• TOC has a focus on process flow and efficiency
• Utilizing these principles, and others, it is possible to optimize processes to increase robustness, throughput, and quality
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Process Controls
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• Site-wide education on TOC/Lean/5S
• Unidirectional, sequential process flow
• Small batch sizes
• Point of use storage
• Visual indicators
• Reduction of non-value added steps
• Samples barcoding
• LIMS
Theory of Constraint measures also reduce process variability as they allow employees to be focused on the task at hand and minimize the chance of error
Sequencing Process Controls
• Utilize data analysis programs to track and trend key assay performance indicators
– Signal/noise ratios of each batch – Percent difference to reference(s) – Length of sequence read – Peak uniformity
• Strict QC system for reagent mixes and lot acceptance
• Optimize personnel and workflow to minimize bottlenecks and meet turnaround times
• Rapidly identify and address potential problems
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Points to Consider • Can apply principals of risk management to the microbial
identification process and your Environmental Monitoring program
• Not all microbial identification technologies are created equal, but by using the more “modern” technologies you can have unparalleled performance and high confidence in the data generated
• The data gathered in your EM and Tracking and Trending programs can be used to document the state of control in your manufacturing facility
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• Monitoring key parameters during the microbial identification process maximizes throughput while maintaining performance
• Assures quality and provides confidence
• The benefits of improving your microbial identification process are increased accuracy, repeatability and reliability
– Increase operational efficiency
– Positive impact on decision making
– Improved compliance position
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Maximize Efficiency and Decrease Process Variability
Thank You!
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Christine Farrance, PhD Director of Research and Development Endotoxin and Microbial Detection | Charles River [email protected] | www.criver.com